The Potential Response of Terrestrial Carbon Storage to Changes in Climate and Atmospheric CO2

We use a georeferenced model of ecosystem carbon dynamics to explore the sensitivity of global terrestrial carbon storage to changes in atmospheric CO₂ and climate. We model changes in ecosystem carbon density, but we do not model shifts in vegetation type. A model of annual NPP is coupled with a model of carbon allocation in vegetation and a model of decomposition and soil carbon dynamics. NPP is a function of climate and atmospheric CO₂ concentration. The CO₂ response is derived from a biochemical model of photosynthesis. With no change in climate, a doubling of atmospheric CO₂ from 280 ppm to 560 ppm enhances equilibrium global NPP by 16.9%; equilibrium global terrestrial ecosystem carbon (TEC) increases by 14.9%. Simulations with no change in atmospheric CO₂ concentration but changes in climate from five atmospheric general circulation models yield increases in global NPP of 10.0–14.8%. The changes in NPP are very nearly balanced by changes in decomposition, and the resulting changes in TEC range from an increase of 1.1% to a decrease of 1.1%. These results are similar to those from analyses using bioclimatic biome models that simulate shifts in ecosystem distribution but do not model changes in carbon density within vegetation types. With changes in both climate and a doubling of atmospheric CO₂, our model generates increases in NPP of 30.2–36.5%. The increases in NPP and litter inputs to the soil more than compensate for any climate stimulation of decomposition and lead to increases in global TEC of 15.4–18.2%.     

Formulation and verification of a land surface parameterization for atmospheric models

The need for a well-defined lower boundary condition for atmospheric numerical models is well documented. This paper describes the formulation of a land surface parameterization, which will be used in atmospheric boundary-layer and mesoscale numerical models. The land surface model has three soil layers for the prediction of soil moisture and soil temperature. Model soil properties depend on soil texture and moisture content. A homogeneous distribution of vegetation is also included, so that transpiration may be included, as well as the interception of precipitation by vegetation elements. The simulated vegetation also affects the mean surface albedo and roughness characteristics.First ISLSCP Field Experiment (FIFE) data are used to verify the model. Three cases during the growing season were chosen, each case having different amounts of vegetation cover. Stand alone simulations, where observations of atmospheric and radiation variables are input to the land surface model, were performed. These simulations show that the model is able to reproduce observed surface energy budgets and surface temperatures reasonably well. The RMS differences between modeled and obsered turbulent fluxes of heat and moisture are quite comparable to those reported by more detailed land surface models.     

Sensitivity study and validation of a land surface parameterization using the HAPEX-MOBILHY data set

A simple parameterization of land surface processes, amenable to the structure of a two-layer soil model, including a representation of the vegetation, has been designed for use in meteorological models. Prior to implementation in a mesoscale model, it is necessary to check the components and to verify the good working order of the parameterization as a whole. The aims of this paper then are: (i) evaluation and a sensitivity study of the various components of the model, specifying the needed accuracy for the parameters; (ii) micrometeorological validation of the model against the HAPEX-MOBILHY data set.First, we present the basic scheme. The focus is on the parameterization of surface resistance, and especially on its relationship with soil moisture.A sensitivity study is then performed through a set of one-dimensional simulations which allow a full interaction between the ground and the atmosphere. Above bare ground, it is shown that both soil texture and initial moisture greatly influence the outcome of the simulation. Latent heat flux ranges from that associated with potential evaporation through a switch-like behavior to that of dry soil. Next, the effects of transpiring vegetation canopies on the physical processes involved and the surface energy balance are examined. The sensitivity of the latent heat flux to changes in the soil and canopy parameters is emphazised; the major influence of the initial mean soil moisture and of the vegetation cover is pointed out. Finally, the evolution of the boundary layer in response to various surface conditions is studied.A validation of the land surface scheme is conducted through daily cycles during cloudless days. Simulated turbulent fluxes are successfully compared to micrometeorological measurements over a maize field at different growth stages. Over a pine forest, the correct simulation of the turbulent fluxes is obtained with an adequate parameterization of the surface resistance accounting for the atmospheric moisture deficit.     

An Investigation of Higher-Order Closure Models for a Forested Canopy

Simultaneous triaxial sonic anemometer velocity measurements vertically arrayed at six levels within and above a uniform pine forest were used to examine two parameterization schemes for the triple-velocity correlation tensor employed in higher-order closure models. These parameterizations are the gradient-diffusion approximation typically used in second-order closure models, and the full budget for the triple-velocity correlation tensor typically employed in third-order closure models. Both second- and third-order closure models failed to reproduce the measured profiles of the triple-velocity correlation within and above the canopy. However, the Reynolds stress tensor profiles (including velocity variances) deviated greatly from the measurements only within the lower levels of the canopy. It is shown that the Reynolds stresses are most sensitive to the parameterization of the triple-velocity correlation in these lower canopy regions where local turbulent production is negligible and turbulence is mainly sustained by the flux transport term. The failure of the third-order closure model to reproduce the measured third moments in the upper layers of the canopy-top contradicts conclusions from a previous study over shorter vegetation but agrees with another study for a deciduous forest. Whether the third-order closure model failure is due to the zero-fourth-cumulant closure approximation is therefore considered. Comparisons between measured and predicted quadruple velocity correlations suggest that the zero-fourth-cumulant approximation is valid close to the canopy-atmosphere in agreement with recent experiments.     

Modeling the Impact of Black Spruce on the Fire Regime of Alaskan Boreal Forest

In the boreal biome, fire is the major disturbance agent affecting ecosystem change, and fire dynamics will likely change in response to climatic warming. We modified a spatially explicit model of Alaskan subarctic treeline dynamics (ALFRESCO) to simulate boreal vegetation dynamics in interior Alaska. The model is used to investigate the role of black spruce ecosystems in the fire regime of interior Alaska boreal forest. Model simulations revealed that vegetation shifts caused substantial changes to the fire regime. The number of fires and the total area burned increased as black spruce forest became an increasingly dominant component of the landscape. The most significant impact of adding black spruce to the model was an increase in the frequency and magnitude of large-scale burning events (i.e., time steps in which total area burned far exceeded the normal distribution of area burned). Early successional deciduous forest vegetation burned more frequently when black spruce was added to the model, considerably decreasing the fire return interval of deciduous vegetation. Ecosystem flammability accounted for the majority of the differences in the distribution of the average area burned. These simulated vegetation effects and fire regime dynamics have important implications for global models of vegetation dynamics and potential biotic feedbacks to regional climate.     

Parameterization of snow-free land surface albedo as a function of vegetation phenology based on MODIS data and applied in climate modelling

The aim of this study was to develop an advanced parameterization of the snow-free land surface albedo for climate modelling describing the temporal variation of surface albedo as a function of vegetation phenology on a monthly time scale. To estimate the effect of vegetation phenology on snow-free land surface albedo, remotely sensed data products from the Moderate-Resolution Imaging Spectroradiometer (MODIS) on board the NASA Terra platform measured during 2001 to 2004 are used. The snow-free surface albedo variability is determined by the optical contrast between the vegetation canopy and the underlying soil surface. The MODIS products of the white-sky albedo for total shortwave broad bands and the fraction of absorbed photosynthetically active radiation (FPAR) are analysed to separate the vegetation canopy albedo from the underlying soil albedo. Global maps of pure soil albedo and pure vegetation albedo are derived on a 0.5° regular latitude/longitude grid, re-sampling the high-resolution information from remote sensing-measured pixel level to the model grid scale and filling up gaps from the satellite data. These global maps show that in the northern and mid-latitudes soils are mostly darker than vegetation, whereas in the lower latitudes, especially in semi-deserts, soil albedo is mostly higher than vegetation albedo. The separated soil and vegetation albedo can be applied to compute the annual surface albedo cycle from monthly varying leaf area index. This parameterization is especially designed for the land surface scheme of the regional climate model REMO and the global climate model ECHAM5, but can easily be integrated into the land surface schemes of other regional and global climate models.     

Evaluating the Dependence of Vegetation on Climate in an Improved Dynamic Global Vegetation Model

The capability of an improved Dynamic Global Vegetation Model (DGVM) in reproducing the impact of climate on the terrestrial ecosystem is evaluated. The new model incorporates the Community Land ModelDGVM (CLM3.0-DGVM) with a submodel for temperate and boreal shrubs, as well as other revisions such as the two-leaf scheme for photosynthesis and the definition of fractional coverage of plant functional types (PFTs). Results show that the revised model may correctly reproduce the global distribution of tempera...     

Development of an establishment scheme for a DGVM

Environmental changes are expected to shift the distribution and abundance of vegetation by determining seedling establishment and success. However, most current ecosystem models only focus on the impacts of abiotic factors on biogeophysics (e.g., global distribution, etc.), ignoring their roles in the population dynamics (e.g., seedling establishment rate, mortality rate, etc.) of ecological communities. Such neglect may lead to biases in ecosystem population dynamics (such as changes in population density for woody species in forest ecosystems) and characteristics. In the present study, a new establishment scheme for introducing soil water as a function rather than a threshold was developed and validated, using version 1.0 of the IAP-DGVM as a test bed. The results showed that soil water in the establishment scheme had a remarkable influence on forest transition zones. Compared with the original scheme, the new scheme significantly improved simulations of tree population density, especially in the peripheral areas of forests and transition zones. Consequently, biases in forest fractional coverage were reduced in approximately 78.8% of the global grid cells. The global simulated areas of tree, shrub, grass and bare soil performed better, where the relative biases were reduced from 34.3% to 4.8%, from 27.6% to 13.1%, from 55.2% to 9.2%, and from 37.6% to 3.6%, respectively. Furthermore, the new scheme had more reasonable dependencies of plant functional types (PFTs) on mean annual precipitation, and described the correct dominant PFTs in the tropical rainforest peripheral areas of the Amazon and central Africa.     

Impact of Spin-up Forcing on Vegetation States Simulated by a Dynamic Global Vegetation Model Coupled with a Land Surface Model

A dynamic global vegetation model (DGVM) coupled with a land surface model (LSM) is generally initialized using a spin-up process to derive a physically-consistent initial condition. Spin-up forcing, which is the atmospheric forcing used to drive the coupled model to equilibrium solutions in the spin-up process, varies across earlier studies. In the present study, the impact of the spin-up forcing in the initialization stage on the fractional coverages (FCs) of plant functional type (PFT) in the subsequent simulation stage are assessed in seven classic climate regions by a modified Community Land Model’s Dynamic Global Vegetation Model (CLM-DGVM). Results show that the impact of spin-up forcing is considerable in all regions except the tropical rainforest climate region (TR) and the wet temperate climate region (WM). In the tropical monsoon climate region (TM), the TR and TM transition region (TR-TM), the dry temperate climate region (DM), the highland climate region (H), and the boreal forest climate region (BF), where FCs are affected by climate non-negligibly, the discrepancies in initial FCs, which represent long-term cumulative response of vegetation to different climate anomalies, are large. Moreover, the large discrepancies in initial FCs usually decay slowly because there are trees or shrubs in the five regions. The intrinsic growth timescales of FCs for tree PFTs and shrub PFTs are long, and the variation of FCs of tree PFTs or shrub PFTs can affect that of grass PFTs.     

LPJ-WHyMe模型对1997～2010年中国东北地区潜在植被分布和碳循环的模拟研究

利用一套高分辨率的气候驱动场和全球动态植被模型LPJ-WHyMe(Lund-Potsdam-Jena-Wetland Hydrology and Methane),模拟了中国东北地区潜在植被分布,并对中国东北地区1997～2010年平均净初级生产力（Net Primary Production, NPP）、净生态系统生产力（Net Ecosystem Production, NEP）、燃烧面积、火灾碳排放、土壤温度和土壤湿度进行了估算。LPJ-WHyMe的特点在于能够描述冻融的物理过程以及土壤中多层的湿度和温度。数值结果表明,在LPJ-WHyMe模型提供的植被功能类型（Plant Function Type, PFT）划分的条件下,中国东北地区主要分布了5种植被功能类型,即温带夏绿阔叶林带、北方常绿针叶林带、北方夏绿针叶林带、北方夏绿阔叶林带和温带草本植物。在研究时间段内,中国东北地区NPP的年平均值为376 g(C) m-2,变化范围在324.15～424.86 g(C) m-2之间。火灾机制的引入使得LPJ-WHyMe模型对NEP的模拟能力进一步提高,即NEP年平均值为42.36 g(C) m-2,表明中国东北地区陆地生态系统总体表现为“碳汇”。中国东北地区年平均燃烧面积分数为0.84%,火灾碳排放量为42.41 g(C) m-2,整体上模型高估了燃烧面积值和火灾碳排放量,模型对东北地区火灾的模拟仍然存在一定的局限性。中国东北地区土壤温度与气温呈正相关关系,且各层土壤温度与气温的相关性随着深度的增加而减弱。中国东北地区土壤湿度与降水呈正相关关系,土壤湿度与气温呈反相关关系。上述结果表明LPJ-WHyMe模型模拟中国东北地区潜在植被分布和碳循环是有效的。     

Modeling bio-geophysical feedback in the African and Indian monsoon region

 An asynchronously coupled global atmosphere-biome model is used to assess the dynamics of deserts and drought in the Sahel, Saudi-Arabia and the Indian subcontinent. Under present-day conditions of solar irradiation and sea-surface temperatures, the model finds two solutions: the first solution yields the present-day distribution of vegetation and deserts and the second shows a northward spread of savanna and xerophytic shrub of some 600 km, particularly in the southwest Sahara. Comparison of atmospheric states associated with these solutions corroborates Charney’s theory of a self-induction of deserts through albedo enhancement in the Sahel. Over the Indian subcontinent, changes in vegetation are mainly caused by a positive feedback between increased soil moisture and stronger summer monsoon. Received: 18 April 1995/Accepted: 17 September 1996     

Determining Effects of Area Burned and Fire Severity on Carbon Cycling and Emissions in Siberia

The Russian boreal forest contains about 25% of the global terrestrial biomass, and even a higher percentage of the carbon stored in litter and soils. Fire burns large areas annually, much of it in low-severity surface fires – but data on fire area and impacts or extent of varying fire severity are poor. Changes in land use, cover, and disturbance patterns such as those predicted by global climate change models, have the potential to greatly alter current fire regimes in boreal forests and to significantly impact global carbon budgets. The extent and global importance of fires in the boreal zone have often been greatly underestimated. For the 1998 fire season we estimate from remote sensing data that about 13.3 million ha burned in Siberia. This is about 5 times higher than estimates from the Russian Aerial Forest Protection Service (Avialesookhrana) for the same period. We estimate that fires in the Russian boreal forest in 1998 constituted some 14–20% of average annual global carbon emissions from forest fires. Average annual emissions from boreal zone forests may be equivalent to 23–39% of regional fossil fuel emissions in Canada and Russia, respectively. But the lack of accurate data and models introduces large potential errors into these estimates. Improved monitoring and understanding of the landscape extent and severity of fires and effects of fire on carbon storage, air chemistry, vegetation dynamics and structure, and forest health and productivity are essential to provide inputs into global and regional models of carbon cycling and atmospheric chemistry.     

陆面过程模式CLM4.5在半干旱区退化草原站的模拟性能评估

利用国际协同强化观测期(CEOP)在中国半干旱区退化草地站——通榆站的观测资料,对一个较为完善的陆面过程模式NCAR_CLM4.5(Community Land Model 4.5)的模拟性能进行检验。模拟结果与观测资料的对比表明,CLM4.5能很好地模拟出观测站点的辐射通量、水热交换、土壤温湿的空间分布和时间变化特征。但地表吸收的辐射模拟值略低,土壤湿度偏低,地表吸收的辐射及土壤温度等日变化略大;大气强迫变量处于某些特定的形势下时,模拟存在较大误差,如8月底的模拟。此外,冬季辐射通量、水热交换以及土壤温湿的模拟均存在较大误差,说明CLM4.5模式在冬季地表物理过程的参数化方案上需要进一步改进。     

Greenhouse gas induced changes in the fire risk in Brazil in ECHAM5/MPI-OM coupled climate model

Vegetation fires are the second largest source of greenhouse gas emissions to the atmosphere. The reduction of the climatic impact of these emissions is related to the vegetation susceptibility to fire (fire risk), as well as to the understanding of possible implications of changes in atmospheric circulation on fire risk in the near-future. This study evaluates the environmental susceptibility to fire occurrence based on a Potential Fire Index (PFI). Two climate simulations from the ECHAM5/MPI-OM climate model have been used to calculate the PFI: present day (1980–2000) and an experiment for the end of the twenty-first century (2080–2100). The results indicate that the proposed PFI methodology could properly reproduce the areas with the highest fire incidence under present conditions. Moreover, it was found that under greenhouse warming conditions the PFI foresees an increase in the fire risk area, particularly for the Amazon region. We concluded, furthermore, that changes of vegetation predicted to occur in the future lead to substantial modifications in the magnitude of the PFI, and may potentially extend the length of the fire season due to induced longer drought periods as compared to current conditions.     

Modeling the eco-hydrologic response of a Mediterranean type ecosystem to the combined impacts of projected climate change and altered fire frequencies

Global Climate Models (GCMs) project moderate warming along with increases in atmospheric CO₂ for California Mediterranean type ecosystems (MTEs). In water-limited ecosystems, vegetation acts as an important control on streamflow and responds to soil moisture availability. Fires are also key disturbances in semi-arid environments, and few studies have explored the potential interactions among changes in climate, vegetation dynamics, hydrology, elevated atmospheric CO2 concentrations and fire. We model ecosystem productivity, evapotranspiration, and summer streamflow under a range of temperature and precipitation scenarios using RHESSys, a spatially distributed model of carbon–water interactions. We examine the direct impacts of temperature and precipitation on vegetation productivity and impacts associated with higher water-use efficiency under elevated atmospheric CO2. Results suggest that for most climate scenarios, biomass in chaparral-dominated systems is likely to increase, leading to reductions in summer streamflow. However, within the range of GCM predictions, there are some scenarios in which vegetation may decrease, leading to higher summer streamflows. Changes due to increases in fire frequency will also impact summer streamflow but these will be small relative to changes due to vegetation productivity. Results suggest that monitoring vegetation responses to a changing climate should be a focus of climate change assessment for California MTEs.     

Boreal forest and tundra ecosystems as components of the climate system

The effects of terrestrial ecosystems on the climate system have received most attention in the tropics, where extensive deforestation and burning has altered atmospheric chemistry and land surface climatology. In this paper we examine the biophysical and biogeochemical effects of boreal forest and tundra ecosystems on atmospheric processes. Boreal forests and tundra have an important role in the global budgets of atmospheric CO₂ and CH₄. However, these biogeochemical interactions are climatically important only at long temporal scales, when terrestrial vegetation undergoes large geographic redistribution in response to climate change. In contrast, by masking the high albedo of snow and through the partitioning of net radiation into sensible and latent heat, boreal forests have a significant impact on the seasonal and annual climatology of much of the Northern Hemisphere. Experiments with the LSX land surface model and the GENESIS climate model show that the boreal forest decreases land surface albedo in the winter, warms surface air temperatures at all times of the year, and increases latent heat flux and atmospheric moisture at all times of the year compared to simulations in which the boreal forest is replaced with bare ground or tundra. These effects are greatest in arctic and sub-arctic regions, but extend to the tropics. This paper shows that land-atmosphere interactions are especially important in arctic and sub-arctic regions, resulting in a coupled system in which the geographic distribution of vegetation affects climate and vice versa. This coupling is most important over long time periods, when changes in the abundance and distribution of boreal forest and tundra ecosystems in response to climatic change influence climate through their carbon storage, albedo, and hydrologic feedbacks.     

Surface radar-derived convective rainfall associations with Midwest US land surface conditions in summer seasons 1999 and 2000

Previous research has suggested that spatial heterogeneities in soil moisture and/or vegetation cover promote the development of convective clouds. We examine the intensity of convective precipitation for the Midwest US Corn Belt in the summers of 1999 and 2000, which had contrasting synoptic circulation, atmospheric humidity, and soil moisture conditions. For days when synoptic scale atmospheric forcing is weak, we calculate a convective severity index (CSI) based on radar reflectivity composite values. Our results suggest that boundaries between soil types, and cropland and forest vegetation types in the western portion of the Corn Belt, enhance the development of convective precipitation. In the eastern part of the Corn Belt, less convection occurs, but we find a positive correlation between the intensity of convection and soil moisture conditions. Our results also demonstrate that the CSI is a simple yet effective technique for identifying where deep convection occurs relative to lighter precipitation.     

Influence of dynamic vegetation on climate change arising from increasing CO<Subscript>2</Subscript>

A dynamic global vegetation model (DGVM) is coupled to an atmospheric general circulation model (AGCM) to investigate the influence of vegetation dynamics on climate change under conditions of global warming. The model results are largely in agreement with observations and the results of previous studies in terms of the present climate, present potential vegetation, present net primary productivity (NPP), and pre-industrial carbon budgets. The equilibrium state of climate properties are compared among pre-industrial, doubled, and quadrupled atmospheric CO₂ values using DGVM–AGCM and current AGCM with fixed vegetation to evaluate the influence of dynamic vegetation change. We also separated the contributions of temperature, precipitation and CO₂ fertilization on vegetation change. The results reveal an amplification of global warming climate sensitivity by 10% due to the inclusion of dynamic vegetation. The total effects of elevated CO₂ and climate change also lead to an increase in NPP and vegetation coverage globally. The reduction of albedo associated with this greening results in enhanced global warming. Our separation analysis indicates that temperature alters vegetation at high latitudes such as Siberia or Alaska, where there is a switch from tundra to forest. On the other hand, CO₂ fertilization provides the largest contribution to greening in arid/semi-arid region. Precipitation change did not cause any drastic vegetation shift.     

Impacts of Climate Change on the Global Forest Sector

The path and magnitude of future anthropogenic emissions of carbon dioxide will likely influence changes in climate that may impact the global forest sector. These responses in the global forest sector may have implications for international efforts to stabilize the atmospheric concentration of carbon dioxide. This study takes a step toward including the role of global forest sector in integrated assessments of the global carbon cycle by linking global models of climate dynamics, ecosystem processes and forest economics to assess the potential responses of the global forest sector to different levels of greenhouse gas emissions. We utilize three climate scenarios and two economic scenarios to represent a range of greenhouse gas emissions and economic behavior. At the end of the analysis period (2040), the potential responses in regional forest growing stock simulated by the global ecosystem model range from decreases and increases for the low emissions climate scenario to increases in all regions for the high emissions climate scenario. The changes in vegetation are used to adjust timber supply in the softwood and hardwood sectors of the economic model. In general, the global changes in welfare are positive, but small across all scenarios. At the regional level, the changes in welfare can be large and either negative or positive. Markets and trade in forest products play important roles in whether a region realizes any gains associated with climate change. In general, regions with the lowest wood fiber production cost are able to expand harvests. Trade in forest products leads to lower prices elsewhere. The low-cost regions expand market shares and force higher-cost regions to decrease their harvests. Trade produces different economic gains and losses across the globe even though, globally, economic welfare increases. The results of this study indicate that assumptions within alternative climate scenarios and about trade in forest products are important factors that strongly influence the effects of climate change on the global forest sector.